The invention pertains to magnetic resonance imaging method to produce successive magnetic resonance images.
Such a magnetic resonance imaging method is known from the paper ‘Unifying linear prior-information-driven methods for accelerated image acquisition’ by J. Tsao et al. in MRM46(2001)652–660.
The known magnetic resonance imaging method concerns an acquisition and reconstruction strategy which aims at faster image acquisition. The known magnetic resonance imaging method is familiar in the technical field of magnetic resonance imaging as Broad-use Linear Acquisition Speed-up Technique (BLAST). In the known method a static reference image is reconstructed from a training set of magnetic resonance signals,                a distribution of likelihood of changes in the successive magnetic resonance images is identified from the static reference image,        a dynamic series of sets of magnetic resonance signals is acquired and        the successive magnetic resonance images are reconstructed from the respective sets of magnetic resonance signals of the dynamic series on the basis of the identified distribution of likelihood of changes, and the static reference image.        
According to the known method sampling of the dynamic series of sets magnetic resonance signals is reduced to speed up acquisition. The sampling of magnetic resonance signals is made quite effective by constraining the reconstruction to regions in which changes are likely. The successive magnetic resonance image are reconstructed on the basis of the static reference image together with the later acquired dynamic series of sets of magnetic resonance signals; this dynamic series adequately take into account changes that have occurred after the acquisition of the training set of magnetic resonance signals which led to the static reference image.
Although the known method successfully reduces the signal acquisition time, it has several known limitations. Firstly, it requires the acquisition of a static reference image, when the object exhibits little or no motion. This may not be possible for applications where continuous motion is involved, such as cardiac imaging. Secondly, the known method assumes that the spatial distribution of likelihood of changes is known, but it does not describe a technique for estimating it. Therefore, the known method is restricted to applications where such spatial distribution can be obtained by other means. Thus, it has appeared that there is an ongoing need to shorten the signal acquisition time in order to better handle rapid and continuous object motion and to further reduce image artifacts.
An object of the invention is to provide a magnetic resonance imaging method which requires the same or an even shorter signal acquisition time relative to the known method, but without the associated restrictions while achieving reduced image artifacts and consequently improved image quality.
This object is achieved according to the invention wherein successive sets of magnetic resonance signals are acquired by successively scanning respective sets of points in k-space such that                the successive scanning builds up sampling of k-space at        the successive scanning covers more frequently a predetermined portion of k-space at full sampling density and        successive magnetic resonance images are reconstructed from the successive sets of magnetic resonance signals.        
According to the invention, full sampling of k-space is built up from the successive sets of magnetic resonance signals, where individual sets of magnetic resonance signals at each instant in time may be undersampled. Accordingly, sampling is built up in time and even full sampling can be achieved as more and more successive sets of magnetic resonance signals are acquired. Further, a predetermined portion of k-space is repeatedly revisited to achieve full sampling of the predetermined portion earlier than the full sampling of k-space as a whole. This fully sampled predetermined portion of k-space is employed as a training dataset on the basis of which aliasing artefacts caused by the undersampling in the individual sets of magnetic resonance signals. Preferably, the predetermined portion of k-space that is repeatedly revisited concerns a central region of k-space, such as one ore several bands in the ky-kz plane located around kz=0 or ky=0.
The invention relies on the insight that magnetic resonance signals are generally concentrated in the central portion of k-space. Hence, by successive sampling of different positions in the central portion of k-space at different instants, the distribution of likelihood of changes can be identified from the training data. This distribution is identified in the space spanned by geometrical space alone or by geometrical space and temporal frequency.
The invention further relies on the insight that by definition, the static reference image does not change over time. Hence, by successive sampling of different positions of k-space at different instants, sampling at full sampling density of k-space is obtained, thus yielding a fully sampled image, which can be used optionally to obtain a static reference image. Then, for the peripheral zones of k-space, or for the entire k-space if the training data are acquired in a separate scan, only a sub-sampled set of magnetic resonance signals may be acquired. This reduces the time required for scanning the periphery of k-space, or in a pre-set available time, the periphery of k-space can be scanned outwardly to a larger extent. Any aliasing or fold-over involved in the magnetic resonance signals from the sub-sampled portion of k-space is lifted on the basis of the identified distribution of likelihood of changes and optionally the static reference image. Full sampling in this respect indicates a sampling density at wavenumber steps less than the reciprocal ‘field-of-view’. Sub-sampling involves a sampling of k-space at at sampling density less than full sampling density.
In a preferred implementation of magnetic resonance imaging method of the_invention is arranged to produce successive magnetic resonance images wherein                two of successive magnetic resonance signals are acquired in separate scans or in the same scan by successively scanning respective sets of points in k-space such that                    the first set successively scans the central portion or other portions of k-space where the magnetic resonance signals are known to be concentrated to yield successive training data            the second set successively scans respective sets of points in k-space in an undersampled fashion to yield a dynamic series of successive undersampled data                        a static reference image is optionally formed from the training set of magnetic resonance signals,        a distribution of likelihood of changes in the successive magnetic resonance images is identified from the static reference image and/or the training data, in the space spanned by geometrical space alone or by geometrical space and temporal frequency, and        the successive magnetic resonance images are reconstructed from the respective sets of magnetic resonance signals of the dynamic series on the basis of the identified distribution of likelihood of changes and if available, the static reference image The likelihood of change is updated from from time point to time point, so that method of the invention takes temporal changes in the likelihood of changes into account.        
In a preferred implementation the central portion of k-space is successively sampled at a higher sampling than the peripheral region of k-space, for example at the full sampling density. The acquired data can then be separated into two sets of magnetic resonance signals for reconstruction: training data and subsampled data. These two sets of data may share some common data points. The training data are used to identify the distribution of likelihood of changes, while the subsampled data are used optionally to determine the static reference image. The static reference image is optionally reconstructed from the training data and/or undersampled data, or from data acquired separately during time periods with little or no motion.
Then, the successive magnetic resonance images are reconstructed from the sub-sampled magnetic resonance signals on the basis of the identified distribution of likelihood of changes and if available, the static reference image. Accordingly, sparse, i.e. sub-sampled, sampling and sampling of the low-resolution of training data from the centre portion of k-space is integrated into a single scan.
In another preferred implementation, the magnetic resonance signals are acquired by way of a receiver antennae system having a spatial sensitivity profile. The antennae system contains a number of signal channels, which process magnetic resonance signals from respective receiver antennae, such as surface coils. Often, the spatial sensitivity profile only shows very slow temporal variations, or the spatial sensitivity profiles does not change with time. Such slow variations may be caused by slight movement of surface coils that are employed as receiver antennae and that are placed on the body of the patient to be examined. Such slight movement may be caused by respiratory motion of the patient to be examined. The spatial sensitivity profile of the receiver antennae system are derived from the static reference images or any time averaged images constructed from the sub-sampled magnetic resonance signals. The temporal averaging for constructing such images should be long enough such that k-space, at least the central portion, has been fully sampled. The successive magnetic resonance images are reconstructed from the sub-sampled magnetic resonance signals also on the basis of the derived spatial sensitivity of the receiver antennae system.
The signal channels process magnetic resonance signals from respective receiver antennae, such as surface coils. For each signal channel, successive sets of magnetic resonance signals are acquired and reconstructed separately and independently on the basis of the training data and optionally the static reference image, both obtained from the data from the same signal channel. This yields a separate series of successive magnetic resonance images for each signal channel. The successive magnetic resonance images from the multiple signal channels are combined without explicit a priori knowledge of the coil sensitivity profile by calculating the root mean square of the image intensity on a voxel-by-voxel basis.
The present invention is particularly advantageously employed in steady-state free processing imaging (SSFP). Power deposition is notably high at stationary magnetic fields of 3T or more, say 7T. The present invention allows substantial reduction in data acquisition, allowing for substantially reduced power deposition.
Further, the present invention appears to operate particularly advantageously when employed in conjunction with a tagging technique, such as CSPAMM. CSPAMM generates a tagging pattern in a region of interest, e.g. in a region that includes the patient's heart. Such tagging techniques have proven to be very valuable in extending the understanding of e.g. cardiac dynamics. CSPAMM tagging can be employed to generate a three-dimensional tagging pattern. Preferably, when the present invention is applied with a tagging technique, in the central region, one or more central bands in ky-kz space are fully sampled, providing the low resolution training data and the outer regions are sub-sampled along a sheared grid pattern in k-t space. A net 2.5 fold reduction in scan time relative to full sampling is achieved.
According to the invention, parallel imaging techniques for the signal acquisition and the reconstruction of the magnetic resonance images are incorporated in the known BLAST method, with extension to k-t space i.e. the space spanned by the wavevectors of the magnetic resonance signals, i.e. k-space and time. The parallel imaging techniques, such as SENSE and SMASH involve receiving the magnetic resonance signals in an undersampled fashion so that the received magnetic resonance signals include superposed contributions from spatial positions that are an integer number of ‘field-of views’ apart. This superposition is then decomposed into contributions for separate spatial position on the basis of the distribution of likelihood of changes, and optionally the static reference image and the spatial sensitivity profile of the system of receiver antennae system: Preferably, a set of surface coils is employed as a receiver antennae system.
For the acquisition of the training set of magnetic resonance signals the acquisition strategy may be chosen from a very wide variety. Some degree of undersampling may be used to reduce the acquisition time for the training set. As the training set is acquired only once, or maybe is refreshed a few times, relatively little time is gained by undersampling the training set. More preferably, the training set is acquired such that the static reference image has a high spatial resolution and has a very low number of artefacts. This is notably achieved in that the training set is acquired with a high k-space sampling density or when some degree of undersampling is employed, unfolding of aliasing artefacts is undone on the basis of a very accurately determined spatial sensitivity profile of the receiver antennae system.
The time required for acquisition of the magnetic resonance (MR) signals is reduced by employing sub-sampling of the MR-signals. Such sub-sampling involves a reduction in k-space of the number of sampled points which can be achieved in various ways. Notably, the MR signals are picked-up through signal channels pertaining to several receiver antennae, such as receiver coils, preferably surface coils. Acquisition through several signal channels enables parallel acquisition of signals so as to further reduce the signal acquisition time.
Owing to the sub-sampling, sampled data contain contributions from several positions in the object being imaged. The magnetic resonance image is reconstructed from the sub-sampled MR-signals on the basis of the the distribution of likelihood of changes, and and optionally the static reference image and a sensitivity profile associated with the signal channels. Notably, the sensitivity profile is for example the spatial sensitivity profile of the receiver antennae, such as receiver coils. Preferably, surface coils are employed as the receiver antennae. The reconstructed magnetic resonance image may be considered as being composed of a large number of spatial harmonic components which are associated with brightness/contrast variations at respective wavelengths. The resolution of the magnetic resonance image is determined by the smallest wavelength, that is by the highest wavenumber (k-value). The largest wavelength, i.e. the smallest wavenumber, involved, is the field-of-view (FOV) of the magnetic resonance image. The resolution is determined by the ratio of the field-of-view and the number of samples.
The sub sampling may be achieved in that respective receiver antennae acquire MR signals such that their resolution in k-space is coarser than required for the resolution of the magnetic resonance image. The smallest wavenumber sampled, i.e. the minimum step-size in k-space, is increased while the largest wavenumber sampled is maintained. Hence, The image resolution remains the same when applying sub-sampling, while the minimum k-space step increases, i.e. the FOV decreases. The sub-sampling may be achieved by reduction of the sample density in k-space, for instance by skipping lines in the scanning of k-space so that lines in k-space are scanned which are more widely separated than required for the resolution of the magnetic resonance image. The sub-sampling may be achieved by reducing the field-of-view while maintaining the largest k-value so that the number of sampled points is accordingly reduced. Owing to the reduced field-of-view sampled data contain contributions from several positions in the object being imaged.
Notably, when receiver coil images are reconstructed from sub-sampled MR-signals from respective receiver coils, such receiver coil images contain aliasing artefacts caused by the reduced field-of-view. From the receiver coil images and the sensitivity profiles the contributions in individual positions of the receiver coil images from different positions in the image are disentangled and the magnetic resonance image is reconstructed. This MR-imaging method is known as such under the acronym SENSE-method. This SENSE-method is discussed in more detail in the international application no. WO 99/54746-A1.
Alternatively, the sub-sampled MR-signals may be combined into combined MR-signals which provide sampling of k-space corresponding to the full field-of-view. In particular, according to the so-called SMASH-method sub-sampled MR-signals approximate low-order spatial harmonics which are combined according to the sensitivity profiles. The SMASH-method is known as such from the international application no. WO 98/21600. Sub-sampling may also be carried-out spatially. In that case the spatial resolution of the MR-signals is less than the resolution of the magnetic resonance image and MR-signals corresponding to a full resolution of the magnetic resonance image are formed on the basis of the sensitivity profile. Spatial sub-sampling is in particular achieved in that MR-signals in separate signal channels, e.g. from individual receiver coils, form a combination of contributions from several portions of the object. Such portions are for example simultaneously excited slices. Often the MR-signals in each signal channel form linear combinations of contributions from several portions, e.g. slices. This linear combination involves the sensitivity profile associated with the signal channels, i.e. of the receiver coils. Thus, the MR-signals of the respective signal channels and the MR-signals of respective portions (slices) are related by a sensitivity matrix which represents weights of the contribution of several portions of the object in the respective signal channels due to the sensitivity profile. By inversion of the sensitivity matrix, MR-signals pertaining to respective portions of the object are derived. In particular MR-signals from respective slices are derived and magnetic resonance images of these slices are reconstructed.
The invention also relates to a magnetic resonance imaging system. It is an object of the invention to provide a magnetic resonance imaging system for carrying out the magnetic resonance imaging methods according to the invention. A magnetic resonance imaging system of this kind is defined in the independent Claim 6. The functions of a magnetic resonance imaging system according to the invention are preferably carried out by means of a suitably programmed computer or (micro)processor or by means of a special purpose processor provided with integrated electronic or opto-electronic circuits especially designed for the execution of one or more of the magnetic resonance imaging methods according to the invention.
The invention also relates to a computer program with instructions for executing a magnetic resonance imaging method. It is a further object of the invention to provide a computer program whereby one or more of the magnetic resonance imaging methods according to the invention can be carried out. A computer program according to the invention is defined in the independent Claim 7. When such a computer program according to the invention is loaded into the computer of a magnetic resonance imaging system, the magnetic resonance imaging system will be capable of executing one or more magnetic resonance imaging methods according to the invention. For example, a magnetic resonance imaging system according to the invention is a magnetic resonance imaging system whose computer is loaded with a computer program according to the invention. Such a computer program can be stored on a carrier such as a CD-ROM. The computer program is then loaded into the computer by reading the computer program from the carrier, for example by means of a CD-ROM player, and by storing the computer program in the memory of the computer of the magnetic resonance imaging system.